High School Physical Sciences Teachers’ Competence in Some Basic Cognitive Skills

The successful implementation of the national high school Physical Sciences curriculum in South Africa, which places strong emphasis on critical thinking and reasoning abilities of students, would need teachers who are competent in cognitive skills and strategies. The main objectives of this study were to test South African high school Physical Sciences teachers’ competence in the cognitive skills and strategies needed for studying Physical Sciences effectively and also to identify possible reasons for their difficulties and suggest methods for overcoming them. The study method used was the analysis of teachers’ answers to questions that were carefully designed to test competence in explanation skills, mathematical skills, graphical skills, three-dimensional visualization skills, information-processing skills and reasoning skills. Seventy-three teachers from about 50 Dinaledi schools in the North West and Kwazulu-Natal provinces were tested. Teachers’ competence was found to be poor in most of the skills tested. About 40 % (average performance in all 14 test questions) of them had difficulty in answering the questions. Teachers’ lack of competence in cognitive skills and strategies would be an important limiting factor in the successful implementation of the Physical Sciences curriculum. An urgent need therefore exists for training teachers to increase their competence in the cognitive skills and strategies that are needed for studying science effectively.Keywords: Cognitive skills, thinking skills, questions testing skills, problem solving, teacher training, high school physical scienc

Applications of MATLAB in Natural Sciences: A Comprehensive Review

In the natural sciences, MATLAB is a versatile and essential tool that has revolutionized research across various disciplines, including physics, chemistry, biology, geology, and environmental sciences. This review paper provides a comprehensive overview of MATLAB's applications in data analysis, modeling, simulation, image processing, computational chemistry, environmental sciences, physics, engineering, and data visualization. MATLAB simplifies data analysis by handling complex datasets, performing statistical analyses, and aiding in tasks like curve fitting and spectral analysis. In modeling and simulation, it enables the creation of predictive models for intricate systems, facilitating simulations of physical processes, ecological dynamics, and chemical reactions. In image processing, MATLAB enhances and analyzes images, benefiting fields such as medical imaging and remote sensing. For computational chemistry, MATLAB offers a rich library of tools for exploring molecular structures and simulating chemical reactions. Environmental sciences rely on MATLAB for climate data analysis and ecological modeling. In physics and engineering, it is invaluable for simulating complex systems and analyzing experimental data. Additionally, MATLAB's data visualization capabilities allow scientists to create compelling visuals for effective communication. While challenges like licensing costs exist, efforts are underway to address these issues and enhance integration with other software, including artificial intelligence and machine learning tools. Overall, MATLAB's computational power and versatility are fundamental to advancing natural sciences research, making it an invaluable resource for scientists and researchers across various disciplines

ImageJ2: ImageJ for the next generation of scientific image data

ImageJ is an image analysis program extensively used in the biological sciences and beyond. Due to its ease of use, recordable macro language, and extensible plug-in architecture, ImageJ enjoys contributions from non-programmers, amateur programmers, and professional developers alike. Enabling such a diversity of contributors has resulted in a large community that spans the biological and physical sciences. However, a rapidly growing user base, diverging plugin suites, and technical limitations have revealed a clear need for a concerted software engineering effort to support emerging imaging paradigms, to ensure the software's ability to handle the requirements of modern science. Due to these new and emerging challenges in scientific imaging, ImageJ is at a critical development crossroads. We present ImageJ2, a total redesign of ImageJ offering a host of new functionality. It separates concerns, fully decoupling the data model from the user interface. It emphasizes integration with external applications to maximize interoperability. Its robust new plugin framework allows everything from image formats, to scripting languages, to visualization to be extended by the community. The redesigned data model supports arbitrarily large, N-dimensional datasets, which are increasingly common in modern image acquisition. Despite the scope of these changes, backwards compatibility is maintained such that this new functionality can be seamlessly integrated with the classic ImageJ interface, allowing users and developers to migrate to these new methods at their own pace. ImageJ2 provides a framework engineered for flexibility, intended to support these requirements as well as accommodate future needs

Diffusion of Big Data in Indian Scientific Literature: Study of Research Productivity and Scientific Collaboration

Purpose: Big data, a buzzword of the present time, is a term used for extremly large data sets generated from the digital process which is not possible to analyze by traditional methods. These data sets are produced by digital devices such as smart phones, remote sensing, camera, microphones, RFID etc. The literature on big data is growing exponentially since 2011. Big data is tending to establish as a very important research field. This paper aims to explore the evolution, growth and scientific collaboration of the Indian publications in the field of big data. Design/methodology/approach: A survey approach is used in the study while data for the study is collected from Scopus database for the year 2001 to 2015. Bibliometric analysis, visualization and mapping software are used to present the current status, growth trends and collaboration in big data research to examine its diffusion in Indian scientific literature. Findings: We found that the big data research in India is gaining momentum and its diffusion and adoption is increasing tremendously. Conference and seminars are used to do social connect and interaction within the research community. The collaboration at institution level is found usual while collaboration at international level is low. Application of big data in health sciences and life sciences is yet to be explored in comparison to the social sciences and physical sciences. Originality/ Value: This paper presents the growth, trends and collaboration in big data literature by the use of sophisticated bibliometric software and visualization software

Physical pixels

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2000.Includes bibliographical references (leaves 48-51).The picture element, or pixel, is a conceptual unit of representation for digital information. Like all data structures of the computer, pixels are invisible and therefore require an output device to be seen. The physical unit of display, or physical pixel, can be any form that makes the pixel visible. Pixels are often represented as the electronically addressable phosphors of a video monitor, but the potential for different visualizations inspires the development of novel phenotypes. Four new systems of physical pixels are presented: Nami, Peano, the Digital Palette and 20/20 Refurbished. In each case, the combination of material, hardware and software design results in a unique visualization of computation. The chief contribution of this research is the articulation of a mode of artistic practice in which custom units of representation integrate physical and digital media to engender a new art.by Kelly Bowman Heaton.S.M

Ohio Educators Respond to Governor Taft’s Initiative for the Third Frontier: A Call for Action

Author Institution: Capital UniversityThe new science frontier requires training students who have the knowledge and skills to work on scientific problems that transcend specific scientific disciplines. A computational studies curriculum integrated into undergraduate science majors can provide the experiences that students need to succeed in the new science frontier. Computational studies is the use of mathematical modeling and computer visualization to solve problems in biological, physical, medical, and behavioral sciences as well as economics, finance, and engineering. A computational studies curriculum is characterized by: 1) the use of computer visualization techniques and mathematical modeling to answer contemporary questions in science, 2) participation in undergraduate research experiences that includes real-world problemsolving with industry partners, 3) engagement in interdisciplinary conversations within cross-functional teams, 4) development of a computational studies thought process, 5) exploration of the creative nature of science, mathematics, and computer science, and 6) communication of science problems and solutions to a variety of audiences. Opportunities for integrating computational studies into science curricula are explored

Geospatial technologies for physical planning: Bridging the gap between earth science and planning

The application of geospatial information technologies has increased recently due to increase in data sources from the earth sciences. The systematic data collection, storage and processing together with data transformation require geospatial information technologies. Rapidly developing computer technology has become an effective tool in design and physical planning in international platforms. Especially, the availability of geospatial information technologies (remote sensing, GIS, spatial models and GPS) for diverse disciplines and the capability of these technologies in data conversion from two dimensions to the three dimensions provide great efficiency. Thus, this study explores how digital technologies are reshaping physical planning and design. While the potential of digital technologies is well documented within physical planning and visualization, its application within practice is far less understood. This paper highlights the role of the geospatial information technologies in encouraging a new planning and design logic that moves from the privileging of the visual to a focus on processes of formation, bridging the interface of the earth science and physical planning